{"title":"Adaptive Fourier Decomposition Based Signal Instantaneous Frequency Computation Approach","authors":"Liming Zhang","country":null,"institution":"","volume":68,"journal":"International Journal of Mathematical and Computational Sciences","pagesStart":1117,"pagesEnd":1123,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/2536","abstract":"There have been different approaches to compute the\r\nanalytic instantaneous frequency with a variety of background reasoning\r\nand applicability in practice, as well as restrictions. This paper presents an adaptive Fourier decomposition and (\u03b1-counting) based\r\ninstantaneous frequency computation approach. The adaptive Fourier\r\ndecomposition is a recently proposed new signal decomposition\r\napproach. The instantaneous frequency can be computed through the so called mono-components decomposed by it. Due to the fast energy\r\nconvergency, the highest frequency of the signal will be discarded by the adaptive Fourier decomposition, which represents the noise of\r\nthe signal in most of the situation. A new instantaneous frequency\r\ndefinition for a large class of so-called simple waves is also proposed\r\nin this paper. Simple wave contains a wide range of signals for which\r\nthe concept instantaneous frequency has a perfect physical sense.\r\nThe \u03b1-counting instantaneous frequency can be used to compute the highest frequency for a signal. Combination of these two approaches one can obtain the IFs of the whole signal. An experiment is demonstrated the computation procedure with promising results.","references":null,"publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 68, 2012"}